code: def handle_worker_exception(e: BaseException, outfile: IO) -> None:
      """
      Handles exception for Python worker which writes SpecialLengths.PYTHON_EXCEPTION_THROWN (-2)
      and exception traceback info to outfile. JVM could then read from the outfile and perform
      exception handling there.
      """
      from pyspark.serializers import (
          write_int,
          write_with_length,
          SpecialLengths,
      )
  
      try:
          exc_info = None
          if os.environ.get("SPARK_SIMPLIFIED_TRACEBACK", False):
              tb = try_simplify_traceback(sys.exc_info()[-1])  # type: ignore[arg-type]
              if tb is not None:
                  e.__cause__ = None
                  exc_info = "".join(
                      traceback.format_exception(type(e), e, tb)
                  )
          if exc_info is None:
              exc_info = traceback.format_exc()
  
          write_int(SpecialLengths.PYTHON_EXCEPTION_THROWN, outfile)
          write_with_length(exc_info.encode("utf-8"), outfile)
      except IOError:
          # JVM close the socket
          pass
      except BaseException:
          # Write the error to stderr if it happened while serializing
          print(
              "PySpark worker failed with exception:", file=sys.stderr
          )
          print(traceback.format_exc(), file=sys.stderr)
  
imports: import copy
  import functools
  import itertools
  import os
  import platform
  import re
  import sys
  import threading
  import traceback
  import typing
  from types import TracebackType
  from typing import Any, Callable, IO, Iterator, List, Optional, TextIO, Tuple, Union
  from py4j.clientserver import ClientServer
  from pyspark.errors import PySparkRuntimeError
  from py4j.java_gateway import JavaObject
label_desc: Use image node_id 8 for calling a global function with example usage: handle_worker_exception(e, outfile) without return types